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Record W2924496822 · doi:10.21037/atm.2019.03.49

Identification of the right cell sources for the production of therapeutically active extracellular vesicles in ischemic stroke

2019· letter· en· W2924496822 on OpenAlex
Bernd Giebel, Dirk M. Hermann

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAnnals of Translational Medicine · 2019
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsnot available
FundersEuropean Regional Development FundEuropean CommissionVolkswagen FoundationStem Cell Network
KeywordsExtracellular vesiclesIdentification (biology)Stroke (engine)ExtracellularCellMedicineCell biologyChemistryBiologyBiochemistryEcology

Abstract

fetched live from OpenAlex

Degenerative brain diseases including ischemic stroke result in the irreversible loss of brain tissue and are mostly associated with persistent neurological deficits. Commonly, the activity of endogenous stem and progenitor cells in these diseases is not sufficient to restore tissue homeostasis and neurological function. It is broadly assumed that the plasticity of endogenous stem and progenitor cells is insufficient in the adult brain to promote tissue remodeling and enable neurological recovery. Consequently, approaches were designed to treat such diseases with stem or progenitor cells assumed to have comparable developmental potentials than the endogenous stem cells.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.439

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.289
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it